Community exposure to arsenic in the Mekong river delta, Southern Vietnam

We examined the daily inorganic arsenic (i-As) intake from drinking water and rice in 45 households (75 individuals) in the An Giang province, Southern Vietnam. The daily i-As intake ranged from 28-102 μg d(-1), equivalent to the daily dose of 0.6-1.9 μg d(-1) kg((body wt))(-1). Increased As concentrations were observed in human hair in the study location. Approximately 67% (n = 44), 42% (n = 28), and 15% (n = 10) of the hair samples had As levels exceeding 1, 3, and 10 μg g(-1), respectively. The total As concentrations in female and male hair correlated well with the total daily i-As intake. Measurement of As concentrations in the hair of people who were consuming or had previously consumed As from contaminated sources may help predict the onset of negative health effects. We suggested an application of the Bayes's theorem to calculate the probability that an individual in a population will acquire a negative health effect, given that the concentration of arsenic in the subject's hair has been determined.     

Evaluation of energy intensity of transport service sectors in Vietnam

This research analyses energy intensity of transport service sectors in Vietnam and its changing trend in the past years using IO tables and LMDI decomposition method. Energy consumption of 38 economic sectors in 2007, 2012 and 2018 is determined, of which transport service sectors were the second largest energy consumer (17.71 Mtoe), occupied 18.5% of total energy consumed in Vietnamese economy in 2018. In terms of energy intensity, a rising trend is seen in all transport service sectors, of which four most important transport services including bus and other road passenger transport, freight transport service by road and pipeline, waterway shipping freight and aviation passenger reached 0.62 kgoe/USD, 0.72 kgoe/USD, 0.60 kgoe/USD and 0.62 kgoe/USD in 2018, respectively. The ineffective structural change and ineffective energy intensity change are the reasons behind the upward trend in these sectors. Using Leontief inverse, the study also unveils how demanded on transport services by other economic sectors in terms of energy and how much energy embodied in all inputs of any economic sector. In order to keep the energy intensity stable and gradually decreasing, the recommendations are focused on effectiveness in structural changes and improvements in energy efficiency.

     

Concentrations,profiles, emission inventory,and risk assessment of chlorinated benzenes in bottom ash and fly ash of municipal and medical waste incinerators in northern Vietnam

Environmental Science and Pollution Research - Concentrations and congener profiles of seven di- to hexachlorinated benzenes (CBzs) were characterized in bottom ash and fly ash samples collected...     

Application of WRF-Chem to simulate air quality over Northern Vietnam

Environmental Science and Pollution Research - The WRF-Chem (Weather Research and Forecasting with Chemistry) model is implemented and validated against ground-based observations for meteorological...     

Production of plant growth–promoting bacteria inoculants from composting leachate to develop durable agricultural ecosystems

Environmental Science and Pollution Research - Composting process of residual organic material generates considerable amounts of liquid leachate which contains high organic load. This waste stream...     

长江口潮滩芦苇根表铁膜磁性特征及其环境意义

湿地植物根表铁膜对包括重金属在内的物质迁移转化具有重要作用,其氧化铁组成研究备受重视,但利用环境磁学方法进行表征的研究还未见报道.本文对长江口潮滩植物芦苇根系及周边沉积物进行了磁学分析,并结合沉积物粒度、漫反射光谱等测试,对芦苇根表铁膜的磁性矿物组成进行了系统研究.结果表明,芦苇根表铁膜磁性矿物主要包括磁铁矿和赤铁矿.由于沉积物不同深度氧化还原环境的不同,铁膜磁性矿物组成存在垂向差异.研究柱样24 cm深度以上,由于相对氧化的环境,铁膜磁性矿物除磁铁矿外,还有较多的赤铁矿贡献;24 cm深度以下,因根系处于相对还原的环境,磁性矿物以磁铁矿为主.与沉积物相比,24 cm以上深度铁膜中亚铁磁性矿物含量较低,24 cm深度以下则相反,反映铁膜和沉积物磁性矿物来源不同.本项研究表明,磁性测量方法有助于认识湿地植物根表铁膜的矿物组成,对湿地生物地球化学过程研究具有重要价值.     

Accuracy improvement of various short-term load forecasting models by a novel and unified statistical data-filtering method

ABSTRACT

Time-series and machine-learning methods are being strongly exploited to improve the accuracy of short-term load forecasting (STLF) results. In developing countries, power consumption behaviors could be suddenly changed by different customers, e.g. industrial customers, residential customers, so the load-demand dataset is often unstable. Therefore, reliability assessment of the load-demand dataset is obviously necessary for STLF models. Hence, this paper proposes a novel and unified statistical data-filtering method with the best confidence interval to eliminate unexpected noises/outliers of the input dataset before performing various short-term load forecasting models. This proposed novel data-filtering method, so-called the data pre-processing method, is also compared to other existing data-filtering methods (e.g. Kalman filter, Density-Based Spatial Clustering of Applications with Noise, Wavelet transform, and Singular Spectrum Analysis). By using an SCADA system?-based database of a typical 22kV distribution network in Vietnam, NYISO database, and PJM-RTO database, case studies of short-term load forecasting have been conducted with a conventional ARIMA model, an ANN forecasting model, an LSTM-RNN model, an LSTM-CNN combined model, a deep auto-encoder (DAE) network, a Wavenet-based model, a Wavenet and LSTM hybrid model, and a Wavelet Neural Network (WNN) model, which are to validate the novel and unified statistical data-filtering method proposed. The achieved numerical results demonstrate which the accuracy of the aforementioned STLF models can be significantly improved due to the proposed statistical data-filtering method with the best confidence interval of the input load dataset. The proposed statistical data-filtering method can considerably outperform the existing data-filtering methods.     

Vision-independent odometry in the ant Cataglyphis cursor

In contrast to flying insects, in which distance estimation is visually mediated, self-induced image motion and use of familiar landmarks are known to play a minor role in ants. Here we show that strictly diurnal Cataglyphis cursor ants can gauge with accuracy the distance they have travelled even in complete darkness in the absence of any other cues, i.e. chemical or protocounting information. Thus, an ants odometer is a vision-independent system based on proprioceptive cues, implicating some form of step counting, which remain to be elucidated.     

Spring abundance and distribution of the ctenophore Pleurobrachia pileus in the Seine estuary: advective transport and diel vertical migration

Several sets of plankton and hyperbenthos samples were collected from the Seine estuary in late May-early June of 1991, 1992 and 1994, and the abundance, size-frequency, horizontal and vertical distribution, and short-term fluctuations of Pleurobrachia pileus (O.F. Müller, 1776) were determined. In the Seine estuary, P. pileus was more abundant than reported for any other European shallow waters. Its depth-averaged density was 33 individuals m^-3 in 1991 and 32 individuals m^-3 in 1992, with a maximum density of 808 individuals m^-3. The ctenophores displayed passive tidal advection and active diel vertical migration. In the outer estuary, high abundances were observed around low tide, and diel vertical migration was very pronounced. However, many individuals remained aggregated near the bottom at all times. In spring, the distribution of P. pileus coincided with the 33 and 150 S isohalines, with high abundances on the marine side of the estuary. It is suggested that aggregation of ctenophores near the bottom and diel vertical migration play an important role in the retention of P. pileus in the estuary. Two schemes of P. pileus life cycle in the Bay of Seine are proposed.